Data is the new oil and its usage has spread across various domains in the modern world. Professionals from various disciplines like banking, marketing, manufacturing, healthcare, and so on are leveraging the potential of data to streamline their business and stay ahead of their competitors in the market.
It is believed that most of the world’s data have generated in the last few years which is the result of the plethora of channels and medium that’s available these days and also the growing popularity of social media. Those channels generate billions of terabytes of data which if mined properly has the potential to achieve groundbreaking results.
Some of the popular terms related to data are Machine Learning, Deep Learning, Artificial Intelligence, Data Science, and so on. These are the mechanisms in which you derive insights from your data. One of the most used applications of AI is in the field of Healthcare.
Artificial Intelligence in Healthcare
The reliance on independent computer intelligence in healthcare by some of the computer generated solutions are gone in the modern generation. Instead, to analyze data and recommend treatments, human-created algorithms are used. The computer could expand and work on the way human brain functions with the help of neural networks which is the core of Deep Learning.
The concept of Deep Learning is getting increasingly popular in the healthcare industry largely due to its ability to extract complex patterns from data and predict state-of-the-art results. The independent operation of neural networks to separate color, size, etc., can give better outcomes. The transformation of diagnostic medicine and also at an individual cell, the search for cancer could be achieved by such new tools.
The evidence-based approaches are the most commonly used Artificial Intelligence applications in the healthcare industry today. The extraction of information and its application could be done when algorithms get data embedded into them by humans. The combination of appropriate chemotherapy drugs could be recommended by reviewing hundreds of treatment alternatives.The team in the Permanente Medical Group created a model which identifies the patients who could be in the ICU tomorrow. Into a computer system, the algorithm was embedded afterward. The hospitalized patient’s health status was continuously monitored. Whenever a patient was at risk, the physicians were alerted. This could help save thousands of lives by notifying the doctors well in advance.
Visual pattern recognition is another methodology which has made significant strides in the healthcare industry. Using the same human heuristic techniques, it could store thousands of images and is accurate than an average physician by 5% to 10%. In the future, the accuracy could be further between the human and the digital eye. With deep learning gaining traction and machines becoming more powerful, diagnostic methods such as CT, MRI, rash identification, microscopic diagnosis, lesion evaluation, the cardiovascular disease would continue to advance.
Detecting Rare Diseases with Artificial Intelligence
A research carried out at the University of Bonn showed that the diagnosis could be improved by combining portrait photos with genetic and patient data. A rare hereditary disease affects almost half a million children worldwide every year. It could be difficult and time-consuming to obtain a definitive diagnosis. This study was carried out with six hundred and seventy-nine patients and hundred and five rare diseases which concluded that rare diseases could be diagnosed effectively and reliably with the help of artificial intelligence.
The combination of portrait photos with generic and patient data is automatically achieved by the neural networks. In the ‘Genetics of Medicine’ journal, the results are presented. Before the correct diagnosis, a long trail and tribulation process has to be followed by patients with rare diseases. For an early therapy, valuable time is needed to avert progressive damage which could be lost.
Prof. Peter Krawitz, demonstrated the quick and effective diagnosis in facial analysis with the help of artificial intelligence. He did this along with some international team of researchers. The six hundred and seventy-nine patient’s data with a hundred and five different diseases were caused by a change in a single gene. Learning difficulties, stunted growth, bone deformation, etc., was included as well. The intellectual disability was a result of Mabry syndrome. Abnormalities are shown in the faces of those who are affected. This could also be referred to the Kabuki syndrome which is the Japanese traditional form of theatre. The eyelids spaces are long, eye-distance is wide and the eyebrows are arched.
All these characteristic features could be detected by the software from the photo. The most likely of diseases involved could be calculated from the data of the patients and genetic symptoms. DeepGestalt, a neural network developed by FDNA which is an Artificial Intelligence and digital health company.
DeepGestalt was programmed after the computer program was trained with thirty thousand pictures of people suffering from syndrome diseases which are rare. The decisive genetic factors could be filtered out with the combination of facial analysis. A higher rate of diagnosis is a result of the reduction of time in data analysis caused after merging data in a neuronal network. This development enables solving various unsolved cases. Patient’s life could be improved by some extent with the help of this.
The approach of the physicians and the health systems supporting them has a lot of difference between them. AI present various solutions to reduce the gulp between them. Physician’s performance could be radically improved by two Artificial Intelligence approaches. Natural Language processing which interprets natural data in the form of speech and text is one of them. Thousands of medical records could be reviewed by it which would help to evaluate patients suffering from multiple illnesses. Another approach would be reinforcement learning where the doctors would be watched by computers working.
A USA based start-up, Forward uses Artificial Intelligence to follow doctors instead of retrospectively extracting and analyzing the data. The physician’s best work is recorded and analyzed by the computers which benefit patients and their colleagues as well. If the worldwide performance matches the top twenty percent, then diseases like infection, cancer, etc., would decrease substantially.
Mathematics is not the biggest barrier to artificial intelligence. However, it is the acceptance of doctor’s intuition instead of the evidence-based solutions causing the barrier. Physicians rarely tend to defer from their beliefs and it would become more difficult in the coming years when the machine would start to loom over their shoulders.
Investment in AI is expected from the businessmen and the entrepreneurs. Medicine could be taken far beyond its current capability with the help of Machine Learning and Artificial Intelligence. To take the best approaches, creating new diagnosis approaches, hundreds of medical problems treatments, and so on could be achieved with the help of AI.
Medical organizations which are integrated and technology-enabled would acquire these advances sooner. On smartphones or tablets, these solutions could be embraced first followed by pattern recognition software. In the future, various Artificial Intelligence tools could be used by patients themselves and take of their lives as they do with other aspects.
Understanding the Fear of Artificial Intelligence
Despite all the advances that Artificial Intelligence has made and still continue to bring in new studies to solve medical cases, there is a certain fear about AI. From nurse-bots to AI wearables, various solutions have been proposed by several tech firms and start-ups which are not transformative. These are not true machine learning approaches and are just algorithmic in nature. Many have failed in pursuit to deliver quality.
There is a fear that humans would be replaced by machines with AI being the next hyped big thing in medicine. However, these features are more of science-fiction. More than the danger, it offers more opportunities. Machine learning tools would soon be an irreplaceable thing to the physicians as the computer speeds increases in the next ten years.
However, there is a difficult truth that we need to accept. There would be a disappearance of some healthcare jobs if the quality is improved and the cost is lowered in healthcare by technology. Within the next twenty years, Artificial Intelligence could take over most of the market. The pressure is now felt by doctors and several health professionals. However, if new systems improve lives, then it would certainly be adopted. The physician’s role would certainly change in the future. However, it’s still a long way to go before the machine could take the role of physicians and show the same level of empathy which the patients expect.
Deep Learning and Artificial Intelligence could produce several states of the art results if used accurately on relevant data. There are several types of research still going on in medical science to see if AI could eradicate several rare diseases. This article covered some of the practices of AI and how it could be used to detect and treat several rare diseases.
Dimensionless has several blogs and training to get started with Python, and Data Science in general.
Follow this link, if you are looking to learn data science online!
Additionally, if you are having an interest in learning Data Science, Learn online Data Science Course to boost your career in Data Science.
Furthermore, if you want to read more about data science, you can read our Data Science blogs here.